From Sanctuary to Abolition: migrant justice organizing in Toronto, Vancouver, Montreal, and Ottawa
Bibliographic record
Abstract
In this dissertation I examine the politics, policies, and practices of sanctuary in Canada. Specifically, I offer the first comprehensive account of how migrant justice activists have understood and approached the work of building sanctuary cities in Toronto, Vancouver, Montréal, and Ottawa. I show how migrant justice activists have been crucial actors in the development and implementation of sanctuary policies and practices in Canada, despite being largely ignored in scholarly literature on the topic. Beyond an analysis of the rich grassroots theories and strategic practices that activists have developed over two decades, I discern and theorize two fundamental approaches activists have taken to building sanctuary cities: demanding "sanctuary from above" and cultivating "sanctuary from below." Both approaches seek to increase access to services for precarious and non-status migrants, but differ in their theory of change and in practice. On the one hand, demanding sanctuary from above seeks to increase access to services by pressuring municipal governments and public service institutions to adopt sanctuary or "access without fear" policy reforms. On the other, building sanctuary from below prioritizes working directly with frontline service providers, advocates, and migrant communities to secure localized access to services, build networks of mutual aid, and cultivate a culture of solidarity with and among precarious and non-status migrantswith or without the presence of a formal sanctuary policy. I find that both approaches contain common potentials and limits that are traceable across the four cities included in this study. I argue that each approach can hold strategic and tactical value in different circumstances, but also note that the sanctuary from below approach appears to hold more potential to achieve the kinds of long-term social transformation that migrant justice activists are committed to achieving. I conclude by theorizing an abolitionist approach to sanctuary organizing. I combine elements of Black liberation, abolitionist, anti-colonial, and no borders scholarship to construct framework to both evaluate past sanctuary policies and practices, as well as offer a radical agenda for future sanctuary organizing.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.019 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".